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X-WR-CALDESC:Events for The European School of Multimodality Imaging & Therapy (ESMIT)
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UID:1946-1739437200-1739548800@esmit.eanm.org
SUMMARY:Artificial Intelligence in Nuclear Medicine – Current Status and Future Perspective
DESCRIPTION:Artificial intelligence with the development of deep learning has found numerous applications in the medical field over the past few years\, including more specifically that of medical imaging. This includes most areas governing the medical imaging process from detector signal processing to image formation and subsequent image processing. The activity of deep learning spans from the more fundamental aspects such as image reconstruction and associated corrections to more clinical applications driven developments such as that of imaging biomarkers and their usage in patient classification for diagnosis or therapy response monitoring. Although most of these developments are still part of active research\, certain software solutions are slowly finding their way in mainstream clinical reality with multiple clinical evaluation studies currently underway. The course will cover an overview of the main developments of deep learning in the different areas of image formation\, processing and associated clinical applications within the field of nuclear medical imaging and associated multimodalities. Certain examples of potential clinical interest will be covered in each of the above-mentioned areas. \n\n\n\n\n\n\n\nRegister nowRegistration now closed. For last minute interest\, please contact esmit@eanm.org \n\n\n\n\n\n\n\n\nLearning Objectives\n\n\n\n\n\nUnderstand the basic principles of deep learning algorithm development\n\n\n\nLearn the latest developments in the use of deep learning for image reconstruction in nuclear and multimodality imaging\n\n\n\nLearn the latest developments in the use of deep learning for image corrections (attenuation\, scatter\, etc) in nuclear and multimodality imaging\n\n\n\nLearn the latest developments in the use of deep learning for image processing (eg. segmentation\, biomarkers) in nuclear and multimodality imaging\n\n\n\nLearn the latest developments in the use of deep learning for potential clinical applications (low dose imaging\, dosimetry\, diagnosis\, predictive and prognostic modeling) in nuclear and multimodality imaging\n\n\n\n\n\n\n\nTarget Audience\n\n\n\n\n\nMedical doctors (nuclear medicine\, radiology)\, Medical Physicists\, Technologists\n\n\n\n\n\n\n\n\n\nProgrammeView the preliminary programme. Please note it is subject to change. View the Programme\n\n\n\n\n\n\n\n\nFaculty\n\n\n\n\n\nStephan NekollaSpeaker \n\n\n\n\n\nMartina SolliniSpeaker \n\n\n\n\n\nDimitris VisvikisSpeaker \n\n\n\n\n\nRegistration Details\n\n\n\nRegistration FeeMode of PaymentCancellation Policy\n\nCourse Fee               € 950.- \n\n\n\nRegistration Fee includes: \n\n\n\n\nElectronic Course Book\, including all Slides\n\n\n\nCoffee & Lunch Breaks on each Course Day\n\n\n\n\nRegistration Fee does NOT include: \n\n\n\n\nTravel to the Venue\n\n\n\nAccommodation\n\n\n\n\n\n\nRegistration fees need to be paid 1 week prior to the event. In case the payment is not received by this deadline\, the registration needs to be cancelled. Payment can be settled by Credit Card Cheques will not be accepted \n\n\n\n\n\nCancellations must be notified in writing to the EANM Office. Telephone cancellations cannot be accepted. Substitutions will be accepted if the name and e-mail address of the substitute are sent to the EANM Office 4 weeks prior to the event. In the case of cancellation 4 weeks before the course\, we will refund you the fee less a € 100\,- administration charge. After this date\, we cannot grant any refund for cancellations. Any refund will take place after the respective course. EANM will not be held liable for cancellation fees of hotels\, airlines or other means of transportation.
URL:https://esmit.eanm.org/event/artificial-intelligence-in-nuclear-medicine-current-status-and-future-perspective/
LOCATION:Future Health Lab\, Alfred-Adler-Straße 1\, Vienna\, 1100\, Austria
CATEGORIES:AI & Quantification,Onsite Course
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